Speaker
Description
Introduction
Wearable brain PET could extend molecular brain imaging beyond conventional fixed scanners by enabling time resolved acquisition in a more flexible form factor. A first technical requirement is to demonstrate interpretable human static images, preservation of relative regional uptake patterns versus a clinical scanner, and stable extraction of dynamic ROI level information.
Methods
Initial human static and dynamic FDG studies were performed with the SmartBrain wearable PET system. For static evaluation, one volunteer received a single 18F-FDG injection of 6.1 mCi. GE DMI PET was acquired at 53 min post injection with an 8 min acquisition, and SmartBrain PET was acquired at 147 min post injection with a 60 min acquisition. Both datasets were registered to MNI space. ROI analysis used the Neuromorphometrics atlas with within-scan whole-brain normalization after exclusion of CSF, ventricular, and vascular labels. For dynamic evaluation, a separate healthy volunteer underwent a 60 min SmartBrain scan. A 2.6 mCi 18F-FDG dose was injected during the first 30 s after scan start. Dynamic framing was 10 s × 12, 30 s × 6, 60 s × 5, and 300 s × 10, yielding 33 frames over 60 min. Representative ROIs included calcarine cortex, middle frontal gyrus, precuneus, putamen, and cerebral white matter.
Results
Static results showed that although the wearable system had shorter axial coverage, intracranial metabolic distribution remained visually interpretable. ROI pattern analysis across 118 atlas-defined regions with a minimum voxel threshold of 200 demonstrated strong agreement between SmartBrain and GE DMI in relative regional uptake pattern, with Spearman = 0.816 and Pearson = 0.843. Bilateral mean ROI values in representative deep gray matter regions, including thalamus, caudate, putamen, and pallidum, also showed good agreement between the two systems. Dynamic results showed that the 33-frame sequence clearly captured tracer arrival, early vascular signal, and gradual accumulation in brain tissue over time. Extracted time activity curves from representative cortical gray matter, deep gray matter, and white matter ROIs were stable and exhibited physiologically plausible regional ordering.
Conclusion
These initial human results demonstrate that the SmartBrain wearable PET system can support both static and dynamic FDG brain imaging. In static imaging, the system showed good agreement with a clinical PET scanner in relative regional uptake pattern. In dynamic imaging, it captured tracer arrival and progressive tissue accumulation and enabled stable ROI-based time activity curve extraction. These findings support the feasibility of wearable human brain PET and provide a foundation for further work on quantitative corrections and future behavioral and clinical applications.
| Track | FTMI |
|---|---|
| Presentation type | Oral |